When to ignore — and believe — the AI hype cycle

The AI hype cycle has been in full swing for several years now, with new breakthroughs and innovations being announced almost daily. From the promise of self-driving cars to the threat of AI taking over human jobs, the media and tech industries have been abuzz with excitement about the potential of artificial intelligence. However, it’s important to remember that not all AI hype is created equal. In this article, we’ll explore when it’s appropriate to ignore the AI hype cycle and when it’s important to believe it.

First, let’s understand what the AI hype cycle is. The Gartner Hype Cycle is a graphical representation of the maturity and adoption of new technologies. It consists of five phases: the Innovation Trigger, the Peak of Inflated Expectations, the Trough of Disillusionment, the Slope of Enlightenment, and the Plateau of Productivity. The AI hype cycle is currently at the peak of inflated expectations, where new technologies and applications are being heavily promoted and investments are pouring in.

However, it’s important to note that not all AI technologies are ready for prime time. Many are still in the early stages of development and may not live up to their promised potential. In fact, Gartner predicts that 85% of AI projects will fail to meet their intended goals by 2022. This doesn’t mean that AI isn’t a promising technology, but rather that it’s important to be discerning when evaluating its potential.

So, when should we ignore the AI hype cycle? Here are some scenarios:

1. When the technology is still in its infancy. As mentioned earlier, many AI technologies are still in the early stages of development. While it’s exciting to think about the possibilities, it’s important to recognize that these technologies may not be ready for widespread adoption just yet.
2. When the claims are too good to be true. If a company is claiming that their AI product can do something that seems impossible or too good to be true, it’s likely that they’re exaggerating its capabilities. It’s important to approach such claims with a healthy dose of skepticism and wait for further evidence before getting on board.
3. When the focus is solely on the technology itself, rather than its practical applications. AI is a tool, not an end goal. While it’s interesting to think about the possibilities of AI, it’s important to remember that its true value lies in how it can be used to solve real-world problems.
4. When the conversation focuses solely on the negative implications of AI. While it’s important to consider the potential risks and downsides of AI, it’s also important to recognize its potential benefits. A balanced conversation that considers both the pros and cons is more productive than one that only focuses on the negatives.

On the other hand, there are times when it’s important to believe the AI hype cycle. Here are some scenarios:

1. When the technology has been proven to work in real-world scenarios. While it’s important to be cautious of unproven technologies, those that have been tested and proven to work in real-world scenarios are more likely to be reliable. For example, AI-powered chatbots have been successfully implemented in customer service industries, and autonomous vehicles are being tested on public roads.
2. When the technology has the potential to solve a pressing problem. AI has the potential to solve some of the world’s most pressing problems, such as climate change, healthcare, and education. If an AI technology is addressing a significant issue and has a clear path to success, it may be worth paying attention to.
3. When the focus is on practical applications rather than theoretical possibilities. As mentioned earlier, AI is a tool, not an end goal. Technologies that focus on practical applications, such as improving healthcare outcomes or streamlining business processes, are more likely to be successful in the long run.
4. When the conversation focuses on the ethical implications of AI. As AI becomes more prevalent in our lives, it’s important to consider its ethical implications, such as privacy, bias, and job displacement. A balanced conversation that considers both the benefits and risks of AI is essential for ensuring that it is developed and used responsibly.

In conclusion, while it’s important to be cautious of the AI hype cycle, it’s also important to recognize its potential value. By understanding when to ignore and believe the hype, we can ensure that AI is developed and used in a responsible and ethical manner that benefits society as a whole.